class_docstr: Identify sentiment-relevant string-level properties of input text.
docstr: Check whether just some words in the input are ALL CAPS
  
  :param list words: The words to inspect
  :returns: `True` if some but not all items in `words` are ALL CAPS
docstr_tok: ["Check","whether","just","some","words","in","the","input","are","ALL","CAPS",":","param","list","words",":","The","words","to","inspect",":","returns",":","`","True","`","if","some","but","not","all","items","in","`","words","`","are","ALL","CAPS"]
code: def allcap_differential(self, words):
      """
      Check whether just some words in the input are ALL CAPS
  
      :param list words: The words to inspect
      :returns: `True` if some but not all items in `words` are ALL CAPS
      """
      is_different = False
      allcap_words = 0
      for word in words:
          if word.isupper():
              allcap_words += 1
      cap_differential = len(words) - allcap_words
      if 0 < cap_differential < len(words):
          is_different = True
      return is_different
  
imports: import math
  import re
  import string
  from itertools import product
  import nltk.data
  from nltk.util import pairwise
label_desc: Use image node_id 4 for calling the SentiText obj's underlying member method code with example usage: obj.allcap_differential(words) and returns: is_different